bert_12_layer_model_v2_complete_training_new_wt_init_120
This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_96 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.3044
- Accuracy: 0.5675
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.5079 | 0.08 | 10000 | 2.4011 | 0.5539 |
2.4953 | 0.16 | 20000 | 2.3921 | 0.5553 |
2.484 | 0.25 | 30000 | 2.3823 | 0.5568 |
2.4828 | 0.33 | 40000 | 2.3711 | 0.5582 |
2.4639 | 0.41 | 50000 | 2.3587 | 0.5598 |
2.4572 | 0.49 | 60000 | 2.3521 | 0.5610 |
2.4385 | 0.57 | 70000 | 2.3430 | 0.5626 |
2.4307 | 0.66 | 80000 | 2.3337 | 0.5633 |
2.4162 | 0.74 | 90000 | 2.3208 | 0.5647 |
2.4088 | 0.82 | 100000 | 2.3133 | 0.5663 |
2.4139 | 0.9 | 110000 | 2.3044 | 0.5675 |
Framework versions
- Transformers 4.30.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
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